Combinatorial serum protein panel ‘promising’ in early HCC detection

Use of a transforming growth factor-beta pathway-based combinatorial serum protein panel may aid in the early detection of hepatocellular carcinoma, according to research presented at The Liver Meeting Digital Experience.

“Current screening of HCC is based on ultrasound and serum alpha-fetoprotein but it has very limited sensitivity. Ideally, we want our new biomarkers to be easy to use and low cost with high sensitivity and specificity; we are still looking for new biomarkers,” Shuyun Rao, MD, of the Feinstein Institutes for Medical Research and Cold Spring Harbor Laboratory, said. “Our hypothesis is proteomic alteration in the pathological state will reflect a function consequence of ongoing biological abnormality to identify tissue and blood-based proteomic biomarkers with a focus on the transforming growth factor-beta (TGF-B) pathway.”

To identify tissue and blood-based combinatorial biomarker panels that aid in the early detection of HCC, researchers evaluated tissue biomarkers using immunohistochemical (IHC) labeling with artificial intelligence validation against 10 functional biomarkers. They performed bioinformatic and statistical analysis on a targeted set of proteins from the TGF-B pathway to identify serum biomarkers. The final studied cohort included 108 biomarkers from 168 patients with cirrhosis (n = 102) and HCC (n = 66).

Following IHC labeling, Rao and colleagues found the expression of TGF-B receptor 2 (TGFBR2) was decreased in tumor tissue compared with cirrhotic samples (P < .02); this was consistent following artificial intelligence validation (P < .002). Further investigation revealed a promising proteomic pattern that differentiated cirrhosis from HCC. Specifically, markers MMP19, BAMBI, IGFBP7, INHBBa, TGFBR3, GDF2, ACVR1B, ADAMtx13, THBS2, CDKN3, CTGF and the mean of COL1A1, COL2A1b and COL3A1 independently predicted HCC in a logistic model with an area under the curve of 0.96. The sensitivity, specific and prediction accuracy of the serum protein panel was 0.81, 0.9 and 0.86, respectively.

“We have found reproducible, functional tissue-based and blood-based biomarkers across multiple sites; it's mainly focused on TGF-B signaling and using this objective tissue-based analysis using artificial intelligence we identify TGFBR2 to be a promising functional predictive HCC tissue biomarker,” Rao concluded. “We also had our targeted analysis identify a panel of 15 TGF-B signaling the protein-based signature could be a promising biomarker for HCC early detection. ... In the future we need to focus on validation of blood-based biomarkers.”